Compressive sensing for small moving space object detection in astronomical images

It is known that detecting small moving objects in as- tronomical image sequences is a significant research problem in space surveillance. The new theory, compressive sensing, pro- vides a very easy and computationally cheap coding scheme for onboard astronomical remote sensing. An algorithm for small moving space object detection and localization is proposed. The algorithm determines the measurements of objects by comparing the difference between the measurements of the current image and the measurements of the background scene. In contrast to reconstruct the whole image, only a foreground image is recon- structed, which will lead to an effective computational performance, and a high level of localization accuracy is achieved. Experiments and analysis are provided to show the performance of the pro- posed approach on detection and localization.

A parallel pipeline connected-component labeling method for on-orbit space target monitoring

The paper designs a peripheral maximum gray differ-ence(PMGD)image segmentation method,a connected-compo-nent labeling(CCL)algorithm based on dynamic run length(DRL),and a real-time implementation streaming processor for DRL-CCL.And it verifies the function and performance in space target monitoring scene by the carrying experiment of Tianzhou-3 cargo spacecraft(TZ-3).The PMGD image segmentation method can segment the image into highly discrete and simple point tar-gets quickly,which reduces the generation of equivalences greatly and improves the real-time performance for DRL-CCL.Through parallel pipeline design,the storage of the streaming processor is optimized by 55%with no need for external me-mory,the logic is optimized by 60%,and the energy efficiency ratio is 12 times than that of the graphics processing unit,62 times than that of the digital signal proccessing,and 147 times than that of personal computers.Analyzing the results of 8756 images completed on-orbit,the speed is up to 5.88 FPS and the target detection rate is 100%.Our algorithm and implementation method meet the requirements of lightweight,high real-time,strong robustness,full-time,and stable operation in space irradia-tion environment.

GS-orthogonalization OMP method for space target detection via bistatic space-based radar

A space-based bistatic radar system composed of two space-based radars as the transmitter and the receiver respectively has a wider surveillance region and a better early warning capability for high-speed targets,and it can detect focused space targets more flexibly than the monostatic radar system or the ground-based radar system.However,the target echo signal is more difficult to process due to the high-speed motion of both space-based radars and space targets.To be specific,it will encounter the problems of Range Cell Migration(RCM)and Doppler Frequency Migration(DFM),which degrade the long-time coherent integration performance for target detection and localization inevitably.To solve this problem,a novel target detection method based on an improved Gram Schmidt(GS)-orthogonalization Orthogonal Matching Pursuit(OMP)algorithm is proposed in this paper.First,the echo model for bistatic space-based radar is constructed and the conditions for RCM and DFM are analyzed.Then,the proposed GS-orthogonalization OMP method is applied to estimate the equivalent motion parameters of space targets.Thereafter,the RCM and DFM are corrected by the compensation function correlated with the estimated motion parameters.Finally,coherent integration can be achieved by performing the Fast Fourier Transform(FFT)operation along the slow time direction on compensated echo signal.Numerical simulations and real raw data results validate that the proposed GS-orthogonalization OMP algorithm achieves better motion parameter estimation performance and higher detection probability for space targets detection.

Space moving target detection using time domain feature

The traditional space target detection methods mainly use the spatial characteristics of the star map to detect the targets, which can not make full use of the time domain information. This paper presents a new space moving target detection method based on time domain features. We firstly construct the time spectral data of star map, then analyze the time domain features of the main objects(target, stars and the background) in star maps, finally detect the moving targets using single pulse feature of the time domain signal. The real star map target detection experimental results show that the proposed method can effectively detect the trajectory of moving targets in the star map sequence, and the detection probability achieves 99% when the false alarm rate is about 8×10^(-5), which outperforms those of compared algorithms.

Micro-Newton scale variable thrust control technique and its noise problem for drag-free satellite platforms:a review

High-precision detection in fundamental space physics,such as space gravitational wave detection,high-precision earth gravity field measurement,and reference frame drag effect measurement,is the key to achieving important breakthroughs in the scientific study of fundamental space physics.Acquiring high-precision measurements requires high-performance satellite platforms to achieve“drag-free control”in a near“pure gravity”flight environment.The critical technology for drag-free control is variable thrust control at the micro-Newton scale.Thrust noise is the most important technical indicator for achieving drag-free flight.However,there is no literature about the current status and future prospects of variable thrust control based on thrust noise.Therefore,the micro-Newton variable thrust control technology and the thrust noise of the drag-free satellite platform are reviewed in this work.Firstly,the research status of micro-Newton scale variable thrust control technology and its applications to drag-free satellite platforms are introduced.Then,the noise problem is analyzed in detail and its solution is theoretically investigated in three aspects:“cross-basin flow problem,”“control problem,”and“system instability and multiple-coupled problem.”Finally,a systematic overview is presented and the corresponding suggested directions of research are discussed.This work provides detailed understanding and support for realizing low-noise variable thrust control in the next generation of drag-free satellites.

The geometric factor of high energy protons detector on FY-3 satellite

Geometric factor is the key parameter for inversion of particle spectrum in space particle detection. Traditional geometric factor is obtained through the method of numerical calculation with the actual structure of the detector as the input condition. The degree of accuracy for data inversion is reduced since traditional geometric factor fails to take into account the physical process of interaction between the particle and substance as well as the influence of factors such as the particle interference between different energy channels on the measurement result. Here we propose an improved geometrical factor calculation method, the concept of which is to conduct actual structural modelling of the detector in the GEANT4 program, consider the process of interaction between the particle and substance, obtain the response function of the detector to particles of different energy channels through the method of Monte Carlo simulation, calculate the influence of contaminated particle on the geometrical factor, and finally get the geometrical factors for different energy channels of the detector. The imrpoved geometrical factor obtained through the method has carried out inversion for the data of high energy protons detector on China's FY-3 satellite, the energy spectrum after which is more in line with the power law distribution recognized by space physics. The comparison with the measured result of POES satellite indicates that the FY-3 satellite data are in good accordance with the satellite data, which shows the method may effectively improve the quality of data inversion.